Article

MiR-29 coordinates age-dependent plasticitybrakes in the adult visual cortexDebora Napoli1,2, Leonardo Lupori1, Raffaele Mazziotti3, Giulia Sagona3,4,5, Sara Bagnoli1 ,

Muntaha Samad6, Erika Kelmer Sacramento7, Joanna Kirkpartick7, Elena Putignano2, Siwei Chen6,

Eva Terzibasi Tozzini8, Paola Tognini1,9, Pierre Baldi6, Jessica CF Kwok10,11, Alessandro Cellerino1,7,†

& Tommaso Pizzorusso1,2,3,*,†

Abstract

Visual cortical circuits show profound plasticity during early lifeand are later stabilized by molecular “brakes” limiting excessiverewiring beyond a critical period. The mechanisms coordinatingthe expression of these factors during the transition from develop-ment to adulthood remain unknown. We found that miR-29aexpression in the visual cortex dramatically increases with age, butit is not experience-dependent. Precocious high levels of miR-29ablocked ocular dominance plasticity and caused an early appear-ance of perineuronal nets. Conversely, inhibition of miR-29a inadult mice using LNA antagomirs activated ocular dominanceplasticity, reduced perineuronal nets, and restored their juvenilechemical composition. Activated adult plasticity had the typicalfunctional and proteomic signature of critical period plasticity.Transcriptomic and proteomic studies indicated that miR-29amanipulation regulates the expression of plasticity brakes in speci-fic cortical circuits. These data indicate that miR-29a is a regulatorof the plasticity brakes promoting age-dependent stabilization ofvisual cortical connections.

Keywords DNA methylation; microRNA; ocular dominance plasticity;

perineuronal net

Subject Categories Neuroscience; RNA Biology

DOI 10.15252/embr.202050431 | Received 14 March 2020 | Revised 4

September 2020 | Accepted 8 September 2020

EMBO Reports (2020) e50431

Introduction

Brain postnatal development is characterized by function-specific

and temporally delimited windows of high plasticity called critical

or sensitive periods, the best known being the natural acquisition of

a language in infants. Ocular dominance (OD) plasticity in the visual

cortex represents the most widely employed paradigm to study criti-

cal periods (CPs). Deprivation of vision from one eye (monocular

deprivation, MD) depresses cortical responses to stimulation of the

deprived eye with maximal effects during the CP for OD plasticity.

This paradigm has been exploited to identify cellular and molecular

mechanisms delimiting CPs. A canonical view posits that OD plastic-

ity decays passively with age; it is becoming increasingly clear,

however, that plasticity levels are set by the coordinated action of

age- and experience-dependent molecular actors actively promoting

or suppressing circuit plasticity (“plasticity brakes”; Hensch & Quin-

lan, 2018; Levelt & Hubener, 2012). These factors regulate different

cellular processes, from transcriptional to translational control, and

can act at different subcellular locations such as intracellular and

extracellular synaptic compartments. For instance, perineuronal

nets (PNNs) enwrapping parvalbumin-positive (PV+) neurons

increase in number and density with age and change their chemical

composition inhibiting OD plasticity in the adult visual cortex (Piz-

zorusso et al, 2002; Carulli et al, 2010; Beurdeley et al, 2012;

Miyata et al, 2012; Rowlands et al, 2018). Epigenetic modifications,

such as histone acetylation and DNA methylation, are also regulated

in coincidence with the closure of the CP (Putignano et al, 2007;

Tognini et al, 2015; Stroud et al, 2017), and their experimental

modulation in adulthood activates levels of plasticity normally

encountered only at the juvenile stage (Putignano et al, 2007;

1 BIO@SNS Lab, Scuola Normale Superiore, Pisa, Italy2 Institute of Neuroscience, National Research Council, Pisa, Italy3 Department of Neuroscience, Psychology, Drug Research and Child Health, NEUROFARBA University of Florence, Florence, Italy4 Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy5 Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy6 Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA, USA7 Leibniz Institute on Aging – Fritz Lipmann Institute (FLI), Jena, Germany8 Stazione Zoologica Anton Dohrn, Naples, Italy9 Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy10 School of Biomedical Sciences, University of Leeds, Leeds, UK11 Institute of Experimental Medicine, Czech Academy of Science, Prague, Czech Republic

*Corresponding author. Tel: +39 0503153167; E-mail: tommaso@in.cnr.it†These authors contributed equally to this work as co-senior authors

ª 2020 The Authors EMBO reports e50431 | 2020 1 of 19

Silingardi et al, 2010; Apulei et al, 2019). However, the upstream

mechanisms coordinating the expression of these seemingly unre-

lated plasticity mechanisms remain unexplored.

MicroRNAs (miRNAs) are short non-coding RNAs that regulate

gene expression by binding mRNAs that show sequence complemen-

tarity, thereby repressing translation and reducing transcript stability

(Bartel, 2018). Since each miRNA can target hundreds of transcripts,

miRNAs can efficiently coordinate different cellular pathways acting

as master regulators of complex biologically processes (Lippi et al,

2016; Rajman & Schratt, 2017). We hypothesized that miRNAs medi-

ate the coordinated age-regulation of different plasticity mechanisms

setting CP timing. Previous work showed that during postnatal

development, there is a dramatic regulation of the mouse visual

cortex transcriptome accompanied by conspicuous changes in

miRNA expression (Mazziotti et al, 2017a). In particular, the most

upregulated miRNA was miR-29a-3p (miR-29a), a member of a

family including miR-29a, miR-29b, and miR-29c. Mir-29 family is

strongly regulated by age across different species and different

tissues (Somel et al, 2010; Ugalde et al, 2011; Baumgart et al, 2012;

Inukai et al, 2012; Takahashi et al, 2012; Fenn et al, 2013; Nolan

et al, 2014). Moreover, it regulates age-dependent processes such as

neuronal maturation (Kole et al, 2011) and aging-associated accu-

mulation of iron in the brain (Ripa et al, 2017). Finally, its predicted

targets show overrepresentation of extracellular matrix remodeling

enzymes and epigenetic factors (Fabbri et al, 2007; Amodio et al,

2015), two classes of molecules regulating the CP for OD plasticity.

Thus, we set to investigate whether miR-29a could act as an age-

dependent regulator of plasticity in the visual cortex.

Results

MiR-29a age-dependent increase controls extracellular matrixand gene transcription regulating factors

In order to unravel key miRNAs that regulate postnatal development

of the visual cortex, we reanalyzed a dataset of coupled miRNA-seq

and RNA-seq in the developing mouse visual cortex (Mazziotti et al,

2017a; Data ref: Mazziotti et al, 2017b). This analysis compared two

time points: postnatal day 10 (P10), immediately before eye opening

and CP onset, and P28, when mouse cortex reaches functional matu-

rity (Espinosa & Stryker, 2012). The miR-29 family, and in particular

miR-29a-3p, was the microRNA with the largest age-dependent

upregulation. Importantly, we found a highly significant overrepre-

sentation of miR-29a-predicted targets among the genes downregu-

lated with age, but not among age-upregulated genes (Fig 1A).

Moreover, we observed that miR-29a targets were selectively down-

regulated with age with respect to all expressed genes (Fig 1B). Age-

dependent downregulation of miR-29a targets was even more

evident for the targets with the strongest support (i.e., top 200 miR-

29a targets according to TargetScan ranking; Fig 1B). These data

suggest that miR-29a contributes to the age-dependent repression of

gene expression by destabilization of its target transcripts.

To gain insights into the molecular consequences of miR-29a

upregulation with age, we performed a gene ontology (GO) overrepre-

sentation analysis of downregulated miR-29a putative targets

using DAVID (Huang et al, 2009a,b). We found a significant overrep-

resentation in the categories related to extracellular matrix

(“metalloendopeptidase activity”, “metalloprotease”, “metallopepti-

dase”) and transcription regulation (“transcription regulation”, “tran-

scription DNA templated”; Fig 1C), including key transcripts such as

Mmps, Adamts, Dnmt3a, Dnmt3b, Tdg, Tet1, Tet2, and Tet3. Both

pathways are well known to regulate OD plasticity of visual cortex

during CP, and their experimental activation in the adult cortex

promotes plasticity (Pizzorusso et al, 2002, 2006; Carulli et al, 2010;

Tognini et al, 2015; Rowlands et al, 2018; Apulei et al, 2019).

To obtain a time-resolved profile of miR-29a expression in the

visual cortex, we performed a qPCR analysis on six time points in an

independent mouse cohort and observed a dramatic 30-fold increase

in mir-29a levels beginning after P10 and reaching a plateau around

P120, when OD plasticity is strongly reduced (Fig 1D). In parallel,

we analyzed the age-dependent regulation of Dnmt3a, a canonical

and well-validated target of miR-29 (Fabbri et al, 2007; Morita et al,

2013; Amodio et al, 2015; Kuc et al, 2017). Dnmt3a expression was

strongly downregulated with age (Fig 1E), and, as shown in Fig 1F,

its levels were negatively correlated with miR-29a levels. To investi-

gate the distribution of miR-29a in visual cortical cells, we performed

in situ hybridization at P25 and P120 using a locked nucleic acid

(LNA) probe recognizing the mature miRNA. The results confirmed

the strong age-dependent upregulation of miR-29a (Fig 1G, N = 3).

Furthermore, at both ages, the vast majority of cortical cells

expressed miR-29a. Considering the importance of PV+ interneurons

in CP regulation (Levelt & Hubener, 2012; Takesian & Hensch,

2013), we specifically investigated miR-29a expression in these cells

by triple staining for miR-29a, PV, and a nuclear marker at P120

(Fig 1H). We found that miR-29a was expressed by many, if not all,

PV+ interneurons (N = 3, 155 PV+ cells, 96.8% mir-29a positive).

The expression of several molecular mediators of visual cortical

plasticity, such as miR-132, Arc, Bdnf, and Npas4, is regulated by

the sensory input (Klein et al, 2007; Gao et al, 2010; Tognini et al,

2011, 2015; Kim et al, 2018). Thus, we investigated the effects of

sensory stimulation on miR-29a expression in four different condi-

tions of experimentally altered visual input: i) dark rearing from

birth (Fig 2A); ii) dark rearing from P10 (Fig 2B); iii) one week in

darkness (P30-P37) followed by 4 h of light exposure (Fig 2C); and

iv) 3 days of MD (P25-P28; Fig 2D). To investigate whether miR-

29a could be regulated by visual experience specifically in PV cells,

we also performed miR-29a in situ coupled with PV staining in dark

reared mice (Fig EV2). The intensity of miR-29a staining within PV

cells and the percentage of PV and miR-29a double-stained cells

were measured. None of these manipulations significantly affected

miR-29a levels, demonstrating that the regulation of miR-29a is

dictated by an intrinsic developmental timing that is not influenced

by visual experience.

Taken together, these results show that miR-29a expression in the

visual cortex is strongly age-dependent and correlates with the plastic-

ity reduction occurring at the end of the CP, naturally leading to the

hypothesis that miR-29a is causally linked to the age-dependent regu-

lation of experience-dependent plasticity in visual cortical circuits.

Increasing miR-29a levels during the CP blocks OD plasticity

If our hypothesis is correct, a premature increase in miR-29a during

CP should be sufficient to reduce plasticity and induce CP closure.

To test this possibility, we experimentally increased miR-29a levels

during CP through intracortical administration of a synthetic

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EMBO reports Debora Napoli et al

A

D

G H

E F

B C

Figure 1. Developmental increase in miR-29a regulates the expression of extracellular and epigenetic remodeling factors..

A Venn diagram showing the intersection between putative miR-29a target genes (gray) and age-upregulated (green, bottom) or age-downregulated (red, top) genes.Ellipse area is proportional to the size of the sets. The numbers indicate the numerosity of the sets. 1,051 miR-29a-predicted targets by TargetScan, 5,429 genesdownregulated with age; 554 genes in the intersection, odds ratio 4.40; Fisher exact test, P < 0.0001; 4,339 upregulated genes with age; 164 genes in theintersection, odds ratio 0.93; Fisher exact test P = 0.427.

B Box plot showing the distribution of log2(FC) of all or selected miR-29a targets in the Data ref: Mazziotti et al, 2017b dataset of age-regulated genes in the visualcortex. Notches represent confidence intervals for the median. Whiskers indicate 95th and 5th percentile, the box marks the 25th and 75th percentile. Significance vs.all detected genes were assessed by Wilcoxon’s test (miR-29a targets P = 4.9 × 10�14, top 200 miR-29a targets P = 3.7 × 10�38).

C DAVID functional annotation clustering analysis showing the most significantly overrepresented GO terms in age-downregulated miR-29 targets.D, E Mature miR-29a (n = 3/4 mice for each age; one-way ANOVA, P < 0.0001; post hoc Tukey’s test ***P < 0.001, ****P < 0.0001, ns not significant) and Dnmt3a

expression level (normalized to P10) at different ages measured by qPCR (n = 3/4 mice for each age; one-way ANOVA, P < 0.0001; post hoc Tukey’s test: *P < 0.05,**P < 0.01, ****P < 0.0001, ns not significant). One-way ANOVA P-values are reported. Error bars represent �SEM.

F Scatter plot showing correlation of miR-29a and Dnmt3a levels in the visual cortex displays a strong negative correlation (Pearson correlation: r = �0.817,P < 0.001). Each circle represents data from a single animal.

G Representative examples of in situ hybridization on visual cortex (left P25, right P120) using a LNA probe against miR-29a. Scale bar 180 lm. Cortical layers aredelimited by roman numerals and brackets

H Example of co-staining for PV (green), miR-29a (red), and nuclear marker (blue) in a P120 mouse. White triangles represent PV+/miR-29a+ cells. Scale bar 20 lm.

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Debora Napoli et al EMBO reports

miR-29a mimic (mim29a) and assessed OD plasticity (Fig 3A). P24

mice were acutely injected with mim29a at three cortical sites

surrounding the binocular visual cortex, as identified by optical

imaging of the intrinsic signal (IOS). Baseline visual responses were

acquired 24 h after injections, and the eyelids of the eye contralat-

eral to the treated cortex were subsequently sutured shut. A second

injection was performed at P26, and OD and molecular analyses

were performed at P28. A separate group of mice underwent the

same procedure but received injections of an oligonucleotide with a

scrambled sequence matching miR-29a nucleotide composition (scr)

and served as controls.

To quantify the efficacy of mim29a treatment, we measured the

levels of miR-29a and of its validated target Dnmt3a at P28 by qPCR.

We detected a near doubling of miR-29a levels and a corresponding

significant decrease in Dnmt3a levels in the visual cortex treated

with mim29a with respect to scr-treated cortex (Fig 3B).

We then assessed OD plasticity by recording IOS elicited by stim-

ulation of either eye twice: before MD at P24 and after MD at P28.

No difference in OD was present between mim29a-treated and scr-

treated mice before MD. However, while in scr-treated mice MD

resulted in a reduction in the OD index (ODI), in mice treated with

mim29a this shift of OD was not observed (Fig 3C). The OD shift

induced by MD in scr-treated mice did not differ from the OD shift

present in naive mice (Fig 3C). The loss of plasticity induced by

miR-29a mimic was confirmed by analyzing the MD regulation of

the molecular plasticity markers Npas4 and Bdnf exon IV in

mim29a-treated mice. The expression of these activity-dependent

transcripts is known to be reduced by MD (Tognini et al, 2015);

however, the amplitude of their downregulation was smaller in

mim29a-treated mice with respect to controls (Fig 3D).

Overall, these data demonstrate that precocious upregulation of

miR-29a is sufficient to close the CP.

MiR-29a antagonization in adult mice promotes OD plasticity

We then tested whether reduction in miR-29a expression in the adult

(P > 120) visual cortex is sufficient to induce OD plasticity. We

injected an antagomiR, an LNA oligonucleotide whose sequence is

complementary to miR29a (amiR-29a) or a control LNA oligonu-

cleotide with a scrambled sequence. LNA oligonucleotides stably

bind their complementary miRNA, thereby blocking its activity and

are resistant to enzymatic degradation. LNAs are extremely well

tolerated and validated; indeed, they are approved for use in humans

(Braasch & Corey, 2001; Khvorova & Watts, 2017; Smith et al, 2019).

Injections were performed at three sites surrounding the binocular

visual cortex identified by IOS imaging. Molecular analyses were

performed seven days after amiR-29a injections (Fig 4A).

To assess the efficacy and the specificity of the amiR-29a treat-

ment, we performed qPCR and RNA-seq analysis from the treated

cortex. qPCR revealed that amiR-29a treatment caused a decrease in

miR-29a and an increase in the miR-29a target Dnmt3a (Fig 4B).

RNA-seq detected 15,303 expressed genes and 1,421 differentially

expressed genes (DEGs) between amiR-29a and control-treated mice

(adjusted P < 0.05), with 985 genes showing upregulation and 430

genes downregulation (Fig 4C; Dataset EV1; Fig EV1). Importantly,

upregulated genes showed a significant overrepresentation of

miR29a targets, but not of targets of other miRNAs (miTEA-miRNA

Target Enrichment Analysis, P < 0.001; Steinfeld et al, 2013; Eden

et al, 2009). Moreover, we observed that miR-29a targets were

upregulated by amiR-29a treatment (Fig 4D) and upregulation was

larger for the top two hundreds miR-29a targets in TargetScan rank-

ing (Fig 4D, Wilcoxon test P = 10�11). We also found that 26% of

the amiR-29a upregulated genes were also significantly downregu-

lated with age in the (Data ref: Mazziotti et al, 2017b) dataset

(Fisher exact test, P < 0.001). Accordingly, miR-29a target genes

that were downregulated with age were selectively upregulated by

amiR-29a treatment (Fig 4F). Again, the effect was more

pronounced in the top two hundreds TargetScan miR-29a targets

(Fig 4F). DAVID analysis revealed that miR-29a targets downregu-

lated with age and upregulated by amiR-29a showed overrepresenta-

tion of the categories “chromatin regulators”, “metalloprotease”,

and “metallopeptidase activity” (Fig 4G). Regulation of transcripts

belonging to these categories was also quantified by qPCR in an

independent cohort of mice detecting a significant increase in the

transcripts coding for matrix metallopeptidases Mmp2, Mmp9, and

Mmp13 (Fig EV3A), and for the epigenetic modifiers Dnmt3a, Tet3,

Gadd45a, and Gadd45b (Fig EV3B). The increased expression of the

canonical miR-29a target DNMT3a was further confirmed at the

protein level by Western blot (Fig EV3C). All these factors were

previously shown to contribute to the developmental regulation of

OD plasticity (Spolidoro et al, 2012; Kelly et al, 2015; Tognini et al,

A B

C D

Figure 2. miR-29a expression is not experience-dependent.

A–D Mature miR-29a expression (miR29) in visually deprived mice: (A) normalrearing (NR, N = 5) vs. dark rearing (DRb, N = 5); t-test, P = 0.19, (B) NR(N = 4) vs. dark rearing from P10 (DRp10, N = 5; t-test, P = 0.70). In bothexperiments, analysis was performed at P25, (C) one week period of darkrearing beginning at P30 (DRw) followed by a 4-h exposure to light(DRw + 4 h light) vs. control animals (ctr, N = 4 for each group; one-way ANOVA, P = 0.68), (D) days of MD beginning at P25, contralateralcortex vs. ipsilateral cortex to deprived eye(N = 5; paired t-test, P = 0.52).Error bars represent �SEM, and symbols represent individual cases.

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EMBO reports Debora Napoli et al

2015; Murase et al, 2017; Apulei et al, 2019), suggesting that the

age-dependent increase in miR-29a initiates and maintains the

repression of plasticity by a coordinated downregulation of these

permissive factors.

Reversal of transcriptome developmental regulation by miR-29a

inhibition could also be observed by global analysis of the cortical

transcriptome after amiR-29a treatment. Indeed, Fig 4H shows that

the fold changes in genes significantly regulated both by age and by

amiR-29a were significantly negatively correlated. Overall, these

data demonstrate that miR-29a inhibition reverses part of the age-

dependent transcriptional program of the visual cortex.

To assess amiR-29a effects at protein level, we performed

proteomic analysis by means of mass spectroscopy-based proteo-

mics with data-independent acquisition (DIA) in a cohort of mice

different from those used for RNA-seq. First, hierarchical clustering

analysis of samples based of protein abundance showed clustering

of animals treated with amiR-29a, demonstrating that the treatment

has a consistent effect on global protein composition in the treated

mice (Appendix Fig S1). Among the 4,595 detected proteins, we

found 359 proteins to be significantly upregulated and 338 proteins

to be significantly downregulated (Dataset EV2, Fig 4C). We

observed that miR-29a targets were selectively upregulated by

amiR-29a treatment also at protein level (Fig 4E). The fold changes

in differentially expressed proteins and transcripts showed a signifi-

cant correlation (Fig 4I, Dataset EV3). To characterize the factors

responsive to amiR-29a, we selected significantly regulated genes

showing a consistent regulation at the protein and transcript level.

DAVID gene ontology analysis of these genes demonstrated an over-

representation of extracellular matrix remodelers and synaptic

proteins (Fig 4J). In light of the expression of miR-29a in PV+ cells,

and the role of these inhibitory neurons in CP closure, we investi-

gated the effect of amiR-29a on this cell population. We used the

single-cell portal for brain research launched by the Broad Institute

of the MIT to visualize the density of regulated proteins in the cell

clusters obtained by single-cell RNA-seq of the adult mouse visual

cortex (Tasic et al, 2016; Fig EV4A). We found that the PV+ cell

class showed the largest enrichment in amiR-29a downregulated

proteins (Fig EV4B). Sensitivity of PV+ cells to miR-29a

A

B C D

Figure 3. miR-29a upregulation blocks OD plasticity of young mice.

A Experimental design for miR-29a mimic treatment in young mice. Primary visual cortex (V1).B MiR-29a and Dnmt3a expression in the cortex treated with scrambled or miR-29a mimic (N = 3 mice). Data were normalized to the untreated cortex of the same

animal. Mir-29a: scr vs. mim29a, t-test, P = 0.005; Dnmt3a scr vs. mim29a t-test, P < 0.0001.C IOS analysis. Ocular dominance index (ODI) of deprived animals treated with scrambled (scr, N = 6 black lines) or miR-29a mimic (mimic29, N = 8 orange lines), or

left untreated (MD no treat, N = 5 gray lines) before and after 3 days of MD. Dashed lines represent single animals, continuous lines the group average. Two-wayANOVA RM, treatment × time, P = 0.028; post hoc Sidak’s comparison, post-MD mim29a vs. scr P < 0.05, mim29a vs. MD no treat P < 0.01; pre-MD scr vs. post-MDscr P < 0.001; pre-MD MD no treat vs. post-MD MD no treat P < 0.01; other comparisons not significant.

D The effects of MD on expression of Npas IV and Bdnf exIV are reported as ratio between expression level of deprived and non-deprived cortex for animals treated withscrambled (scr+MD) and miR-29a mimic (mim29a+MD). Each symbol represents the result of a single mouse. (MD+scr vs. MD+mim29a; N = 4; t-test, Npas4:P = 0.038; Bdnf exIV: P = 0.049). Data information: Error bars represent �SEM, asterisks statistical significance, *P < .05, **P < 0.001, ***P < 0.001.

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Debora Napoli et al EMBO reports

antagonization was also confirmed by the analysis of PV labeling in

visual cortical sections (Fig EV4C) revealing a preserved density of

PV+ cells, but a significant shift (Mann–Whitney test, P < 0.0001)

of PV labeling intensity toward lower levels in the amiR-29a-treated

visual cortex (Fig EV4D).

To test whether miR-29a adult levels repress OD plasticity, we

injected adult (P120) mice with amiR-29a or control LNA. Three

days later, the eye contralateral to the treated cortex was sutured

and molecular and functional assessments were performed after

four days of MD (scheme in Fig 4A). The amplitude of the cortical

response to visual stimulation of the deprived and the non-deprived

eye was quantified by both visual evoked potential (VEP) recordings

and IOS imaging.

VEPs showed a significant reduction in the ratio between the

responses to the deprived and the non-deprived eye in mice treated

with amiR-29a LNA, but not in control mice (Fig 5A). IOS analysis

confirmed the presence of OD plasticity in amiR-29a-treated mice as

shown by the significant change in ODI after MD (Fig 5B). In addi-

tion, IOS revealed that no difference in visual responses of amiR-29a

and control mice was detectable before MD, hence excluding the

A

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E

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IH J

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Figure 4.

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EMBO reports Debora Napoli et al

possibility that the observed effects are due to changes in cortical

responses to visual stimulation of the contralateral eye induced by

amiR-29a. Thus, both VEPs and IOS performed in two separate

cohorts of mice confirmed activation of OD plasticity in adult mice

by miR-29a inhibition.

Common functional and molecular signatures of OD plasticityduring the CP and after miR-29a inhibition in adult mice

Previous work suggested that MD of short duration during the CP

results in selective depression of deprived eye responses (Frenkel &

Bear, 2004; Sato & Stryker, 2008). Thus, we investigated whether

this mechanism underlies also adult OD plasticity elicited by amiR-

29a. We found that OD shift induced by MD in amiR-29a-treated

mice was due to decreased amplitude of cortical responses to stimu-

lation of the deprived eye (Fig 5C and D), with no effects on

responses to stimulation of the non-deprived eye (Fig 5C and E).

These data demonstrate that adult OD plasticity induced by amir-

29a and CP plasticity share similar physiological mechanisms.

We then set to investigate whether CP plasticity and plasticity

induced in the adult visual cortex by miR-29a antagonization also

share key molecular features. We initially studied two activity-

dependent genes (Npas4 and Bdnf exIV) robustly downregulated by

MD during CP (Fig 3D) and found that MD repressed their expres-

sion in amiR-29a-treated mice as well (Fig 5F). To obtain a global

and unbiased comparison of the molecular signature of amiR-29a-

induced plasticity and CP plasticity, we performed label-free mass

spectrometry-based proteomic analyses of MD visual cortices during

CP or in adulthood after treatment with amiR-29a (Datasets EV4 and

EV5). A total of 2,170 proteins were quantified in mice during the

CP, and 168 proteins resulted to be significantly regulated by MD

(P < 0.05). The same analysis in adult mice treated with amiR-29a

enabled the quantification of 1,871 proteins, out of which 199 were

significantly regulated by MD (P < 0.05). We then tested the correla-

tion in the fold changes induced by MD in the two datasets includ-

ing all proteins with log2(FC) > 0.1 in both conditions (N = 149)

and detected a significant positive correlation (Fig 5G; Dataset EV6),

indicating that MD induced a similar regulation of the proteome in

the two datasets.

Proteins were further subdivided into two subgroups based on

the concordance of their regulation in the two datasets, and a GO

overrepresentation analysis was performed on each protein

subgroup using REACTOME (Jassal et al, 2019) as reference. No

significant overrepresentation of terms was detected for the discor-

dant proteins set. By contrast, the concordant protein set showed a

significant overrepresentation of OD plasticity-related terms such as

“CREB phosphorylation through the activation of CaMKII” (R-MMU-

442729), “unblocking of NMDA receptor” (R-MMU-438006), “trans-

mission across chemical synapses” (R-MMU-112315; Fig EV5; Levelt

& Hubener, 2012), mostly belonging to excitatory synapses

(Fig EV5, Dataset EV6). To get a more specific insight into synaptic

proteins, we analyzed concordant and discordant proteins using

SynGo, a new curated database of proteins involved in synaptic

functions and plasticity (Koopmans et al, 2019). Highly significant

enrichment was detected only for concordant proteins, for which a

significant overrepresentation of presynaptic and post-synaptic

proteins was present (Fig 5H and I). A full list of the significant cate-

gories is shown in Datasets EV7 and EV8. Thus, the mechanisms

underlying OD plasticity induced by miR-29a antagonization in the

adult visual cortex activate molecular processes similar to those

activated during CP plasticity.

miR-29a age-dependent expression regulates PNN structure andchemical composition

In order to understand the mechanisms by which juvenile and adult

miR-29a levels affect OD plasticity, we investigated PNN organiza-

tion after experimental modulation of miR-29a levels in the visual

cortex of juvenile and adult mice. Indeed, previous work had shown

that maturation of PNN enwrapping the soma of PV+ cells determi-

nes the closure of the CP for OD plasticity (Pizzorusso et al, 2002,

2006; Carulli et al, 2010; Beurdeley et al, 2012; Lensjø et al, 2017;

Rowlands et al, 2018; Boggio et al, 2019). Moreover, our data show

that age- and miR-29a-regulated genes are enriched in extracellular

◀ Figure 4. Transcriptomic and proteomic effects of miR-29a downregulation.

A Experimental design for amiR-29a treatment in adult mice.B Effects of amiR-29a on the expression of miR-29a and Dnmt3a. Fold change values with respect to the contralateral untreated cortex are reported (�SEM) for mice

treated with amiR-29a or scr. scr vs. amiR-29a; N = 3 t-test, miR-29a **P = 0.0010; Dnmt3a ****P = 0.0019.C Distribution of log2(FC) for the significant cases in transcriptomics (N = 4 scr-treated and N = 3 amiR-29a-treated biological replicates) and proteomics (N = 4

biological replicates per group) datasets of animals treated with amiR-29a versus scr animals. The black line represents the average.D, E Box plot showing distribution of log2(FC) of miR29a targets as (D) transcripts (RNA) and (E) proteins (PROT) in transcriptomic and proteomic datasets of adult

animals treated with amiR-29a. Notches correspond to confidence intervals of the median. Whiskers indicate 95th and 5th percentile, and the box marks the 25th

and 75th percentile. Significance vs. all detected genes and proteins, respectively, assessed by Wilcoxon’s test (P-values shown in figure).F Box plots reporting distribution of log2(FC) of age-downregulated miR29a targets after amiR-29a treatment (N = 4 scr-treated and N = 3 amiR-29a-treated

biological replicates). Notches correspond to confidence intervals of the median. Whiskers indicate 95th and 5th percentile, and the box marks the 25th and 75th

percentile. Significance was assessed with Wilcoxon’s test (P-values shown in figure).G DAVID functional annotation clustering analysis showing the most significantly overrepresented GO terms of miR29a targets downregulated with age and

upregulated by amiR-29a treatment.H Scatter plot correlating the expression changes in genes significantly regulated by age (log2FC, x-axis) and miR-29a antagonization by amiR29a in adult mice

(log2FC, y-axis). (Spearman r = �0.22 P = 1.4 × 10�8; Fisher test showing significant enrichment in the IV quadrant P = 2.2 × 10�16). The number of genes foreach quadrant is reported in figure.

I Scatter plot correlating the expression changes induced by miR-29a antagonization in adult mice at the transcript level (log2FC, x-axis) and protein level (log2FC, y-axis). Spearman coefficient correlation, r = 0.11; P = 0.006, Fisher test showing significant enrichment in the I quadrant P = 0.03. The number of genes for eachquadrant is reported in figure.

J DAVID functional annotation clustering analysis showing the most overrepresented GO terms among genes showing consistent regulation at the transcript andprotein level.

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Debora Napoli et al EMBO reports

remodeling factors and that the PV+ cells show significant

proteomic modulation by amiR-29a (Fig 1C, Figs EV3A and EV4).

Thus, we stained PNNs using Wisteria floribunda agglutinin

(WFA) both in juvenile mice treated with mim29a and in adult

mice treated with amiR-29a (Fig 6A). PNN density was not dif-

ferent between juvenile mice treated with mim29a or scr (Fig 6B);

however, a significant increase in PNN intensity (Fig 6C) was

present in the mim29a-treated group. Subdividing the distribution

of PNN intensity in tertiles corresponding to strong, medium, and

faint PNNs, we observed a significantly higher fraction of strong

PNNs in miR-29a mimic-treated mice as compared to controls

(Fig 6D and E). A high fraction of strongly labeled PNNs is typical

of adult mice expressing low OD plasticity levels (Pizzorusso et al,

2002). Thus, premature adult-like levels of miR-29a resulted in

PNN early maturation.

To test whether the high levels of miR-29a observed in adult

mice are necessary to maintain the mature PNN structure, we

analyzed PNNs in adult mice treated with amiR-29a. AmiR-29a

treatment resulted in a reduction in PNN density (Fig 6F and G) and

intensity (Fig 6H), determining a lower fraction of strong PNNs

(Fig 6I and J). Age-dependent PNN maturation also involves

changes in glycosaminoglycan (GAG) sulfation of chondroitin

sulfate proteoglycans (CSPGs), mainly consisting in a shift from

GAG sulfation in 6 position (C6S) to sulfation in 4 position (C4S;

Foscarin et al, 2017). Previous work showed that restoring the juve-

nile form of GAG sulfation promotes plasticity in the adult visual

cortex and renders CSPGs more permissive to axon growth, regener-

ation, and plasticity (Miyata et al, 2012; Yang et al, 2017). Thus, we

tested whether amiR-29a modifies PNNs also by reducing the adult

C4S form of GAG sulfation. Biochemical analyses showed a

A

D

G H I

E F

B C

Figure 5.

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significant decrease in C4S in adult animals treated with amiR-29a

(Fig 6K; ng of C4S/ug normalized to untreated cortex for scr and

amiR-29a mice), suggesting a reduced inhibitory action on plasticity

of the residual PNNs present in the amiR-29a-treated cortex. C4S

decrease was associated with a significant increased abundance of

arylsulfatase B (ARSB), the enzyme that catalyzes the removal of 4-

sulfation from C4S (Yoo et al, 2013; Zhang et al, 2014), measured

by mass spectrometry and independently confirmed by Western blot

(Fig 6L). Thus, reducing the levels of miR-29a in the adult visual

cortex promotes CP plasticity mechanisms by acting both on PNN

condensation and on chemical composition.

Discussion

The development and differentiation of neurons is clearly coordi-

nated by a set of genes that act as master regulators. Although matu-

ration of neuronal circuits is also a tightly coordinated processes,

our knowledge of the gene networks that set the pace of neuronal

maturation is very limited. In our work, we identify the microRNA

family miR-29 as an age-dependent regulator of developmental plas-

ticity in the visual cortex.

The regulation of miR-29 family is strikingly conserved; its

members are upregulated with age in fish, mice, and humans and in

tissues as diverse as heart, skeletal muscle, aorta, skin, liver,

kidney, lung, sympathetic neurons, and different brain regions

(Somel et al, 2010; Ugalde et al, 2011; Baumgart et al, 2012; Inukai

et al, 2012; Takahashi et al, 2012; Fenn et al, 2013; Nolan et al,

2014). Overexpression of miR-29 family members induces prema-

ture maturation of sympathetic neurons (Kole et al, 2011), and

knock-down of miR-29 family members modifies age-related pheno-

types in fish brain (Ripa et al, 2017) and heart (Heid et al, 2017). In

the visual cortex, miR-29a is the most upregulated miRNA during

CP with a 30-fold increase between P10 and P120. In addition, more

than half of miR-29-predicted targets are downregulated with age,

including key regulators of plasticity, suggesting that miR-29a acts

as a central hub to coordinate expression of apparently unrelated

downstream pathways that remodel the epigenetic landscape and

the composition of the extracellular matrix. Indeed, we showed that

experimental modulations of miR-29a action mimicking adult or

juvenile levels of miR-29a induce corresponding heterochronic

levels of OD plasticity. Premature increase in miR-29a levels in

young mice blocked juvenile OD plasticity, while miR-29a inhibition

in adult animals reversed developmental downregulation of miR-

29a targets and induced a form of OD plasticity endowed with the

typical physiological and proteomic signature of CP plasticity.

To characterize the global molecular correlates of miR-29a action

on OD plasticity, we performed transcriptomic and proteomic analy-

ses after amiR-29a treatment in adult mice. The results showed a

remarkable convergence of miR-29a action on plasticity brakes

controlling plasticity levels by acting on different cell functions and

compartments. For example, previous work showed that OD plastic-

ity can be promoted in the visual cortex by inhibiting epigenetic

enzymes decreasing histone acetylation such as HDACs, or activat-

ing DNA methylation regulatory pathways involving Gadd45b/g and

Tets (Putignano et al, 2007; Silingardi et al, 2010; Apulei et al,

2019). Importantly, the results of these interventions restore the

malleable epigenetic control of chromatin typical of juvenile animals

(Putignano et al, 2007; Tognini et al, 2015; Baroncelli et al, 2016;

Vierci et al, 2016; Stroud et al, 2017). Our analysis reveals that miR-

29a controls the levels of several plasticity-related epigenetic

enzymes. Indeed, miR-29a levels are tightly correlated with Dnmt3a

and that the manipulation of miR-29a levels dramatically affects

Dnmt3a; Tet1, Tet2, Tet3, and Gadd45a and Gadd45b. Moreover,

antagonization of miR-29a also resulted in induction of Arc, a gene

capable of activating OD plasticity in the adult (McCurry et al, 2010;

Jenks et al, 2017), and other plasticity factors such as Egr-1 and Egr-

2, Arpc3, Grin2b, Nr4a1, and Nr4a2 (Knapska & Kaczmarek, 2004;

Lippi et al, 2011; Chen et al, 2014; Mo et al, 2015). Furthermore,

our work shows that miR-29a level is a critical determinant of PNN

maturation, another important plasticity brake in the visual cortex

(Pizzorusso et al, 2002, 2006; Carulli et al, 2010; Lensjø et al, 2017;

◀ Figure 5. miR-29a downregulation promotes experience-dependent plasticity in adult mice with similar physiological and proteomics features of juvenilemice.

A VEP analysis. Ratio between contralateral and ipsilateral eye responses (C/I ratio � SEM) in animals treated with saline and not deprived (sal no MD), withscrambled LNA and MD (scr MD), with amiR-29a LNA and MD (amiR-29a MD). N = 6/7; one-way ANOVA, P = 0.0003; post hoc Tukey’s test: sal noMD vs. scr+MD, ns;sal noMD vs. amiR-29a+MD, P = 0.0002; scr+MD vs. amiR-29a+MD, P = 0.0169.

B IOS analysis. ODI � SEM of deprived animals treated with scr (N = 5, black lines) and amiR-29a LNA (N = 6, blue lines). Dashed lines connect pre- and post-MD ODIvalues of each animal. Solid lines represent the group average. Two-way ANOVA RM, treatment × time, P = 0.0074; post hoc Sidak’s test, pre-MD scr vs. post-MDscr, ns; pre-MD vs. post-MD amiR-29a, P = 0.0005.

C IOS amplitude (� SEM) in response to contralateral eye (contra) and ipsilateral eye (ipsi) stimulation. Other conventions as in (B). amiR-29a (N = 6) vs. scr (N = 5).Contra eye: two-way ANOVA RM, time × treatment interaction P = 0.034; post hoc Sidak’s test; pre-MD vs. post-MD scr, ns; pre-MD vs. post-MD amiR-29a,P = 0.0008. Ipsi eye: two-way ANOVA RM, time × treatment interaction, ns.

D Average time course of the IOS response to visual stimulation of the contralateral eye (contra) pre- and post-MD (thick black line). Gray area delimited by thin blacklines envelops traces from scr animals (95% confidence interval); blue area envelops traces from amiR-29a animals (95% confidence interval).

E Same as in (D) for ipsilateral eye (ipsi) pre- and post-MD responses.F The effects of MD on Npas IV and Bdnf exIV expression are reported as the ratio between expression levels of deprived and non-deprived cortex for animals treated

with scrambled (scr+MD) and amiR-29a (amiR-29a+MD). Each symbol represents the result of one animal. Error bars represent �SEM. scr vs. amiR-29a; t-test;N = 7–9, Npas4: P = 0.035; N = 4–5; Bdnf exIV: P = 0.026.

G Scatter plot correlating the changes in protein abundance induced by MD in young mice (MD CP, x-axis) with the effects observed in the adult deprived micetreated with amiR-29a (MD+LNA_AD, y-axis). Proteins present in both datasets and showing an absolute expression fold change (FC > 0.1) are represented. Greensymbols correspond to proteins with concordant direction of regulation; red symbols correspond to discordant regulation. Pearson correlation: r = 0.19, P = 0.019.The number of genes in each quadrant is reported in figure.

H, I Hierarchical dendrograms of synaptic proteins (SynGO database) showing significant enrichment by color-code: (H) proteins with concordant regulation. (I) proteinswith discordant regulation. Data information: Asterisks report statistical significance, *P < 0.05, ***P < 0.001.

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Debora Napoli et al EMBO reports

Rowlands et al, 2018), and in other brain areas (Fawcett et al, 2019;

Reichelt et al, 2019). PNNs are specialized extracellular matrix

structures predominantly associated with PV+ interneurons in the

visual cortex. They have essentially two structural roles: acting as

scaffold for plasticity by regulating the binding of molecules such as

Otx2 (Beurdeley et al, 2012; Spatazza et al, 2013) and Sema3a

A

C

F

H

K L

I J

G

D E

B

Figure 6.

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(Boggio et al, 2019), and limiting new synaptic connections

(Faini et al, 2018). Adult mice treated with amiR-29a strongly

upregulate extracellular matrix remodelers like MMP2, MMP13,

and MMP9 and reduce PNN intensity and density, while young

animals treated with miR-29a mimic display a premature increase

in PNN intensity. Mir-29a also regulated the age-related changes

in chemical composition of PNNs. Downregulation of miR-29a in

adult mice caused a reduction in sulfonation of chondroitin

sulfate in position 4 (C4S), a chemical modification of CSPGs

typically enriched in adult brain and associated with reduced

axon growth, regeneration, and OD plasticity in the visual cortex

(Miyata et al, 2012; Foscarin et al, 2017; Yang et al, 2017). This

decrease is accompanied by upregulation of ArsB (Bhattacharyya

et al, 2015), the enzyme responsible for removal of sulfate

groups from C4S. Extracellular matrix modulation could also

affect excitatory cells; indeed, extracellular proteolytic activity is

involved in regulating dendritic spine dynamics (Mataga et al,

2004; Oray et al, 2004; Spolidoro et al, 2012). These data indicate

that miR-29a modulation of extracellular matrix could be

involved in miR-29a regulatory action on plasticity; however,

further work clarifying the causal relationship between the PNN

alterations induced by miR-29a/amiR-29a and OD plasticity is

needed. Overall, these data indicate that miR-29a coordinates

the age-dependent regulation of several molecular pathways

regulating CP plasticity.

Importantly, miR-29a expression is not regulated by visual expe-

rience, suggesting that miR-29a is a specific mediator of the action

of age on CP timing. Thus, its action must be integrated with experi-

ence-dependent signals unrelated to miR-29a, such as NARP and

BDNF (Huang et al, 1999; Gu et al, 2013), to achieve input specific

plasticity and experience-dependent regulation of CP. Mir-29a could

act on CP timing also by interacting with circadian clock mecha-

nisms. Indeed previous work showed that clock mutation in PV cells

causes an altered CP (Kobayashi et al, 2015), and miR-29a has been

shown to affect circadian rhythmicity period through regulation of

Per1 and Per2 mRNA stability and translation (Chen et al, 2013). In

support of this hypothesis, Per1 was also strongly upregulated by

amiR-29a in our dataset.

Although mir-29a is broadly expressed in different cell types in

the visual cortex, several data indicate that the effects miR29a on

OD plasticity could involve PV cells. Our in situ hybridization and

previous expression profiling data obtained with Ago-CLIP (He et al,

2012) showed that PV cells express high levels of miR-29a. Further-

more, the time course of cortical miR-29a expression is correlated

with the maturation of WFA-positive PNNs enwrapping PV cells,

while increasing or antagonizing miR-29a correspondingly modu-

lated PV cell PNNs. PV levels were also downregulated by miR-29a

antagonization in adult animals, and bioinformatic analysis of

proteomic data showed that PV cells represent the most affected cell

population in terms of protein downregulation after amiR-29a treat-

ment. Thus, PV cells could be a relevant cellular target for miR-29a

action on CP timing, although further experiments are necessary to

fully clarify this point.

The observation that miR29a is a remodeler of PNNs opens

novel and exciting therapeutic perspective for miR-29a and other

miR-29 family members. Indeed, manipulations of PNNs, both

PNN increase and decrease depending on the type of pathological

condition, have been proposed as possible therapy for several

diseases including schizophrenia, autism, genetic encephalopa-

thies, addiction, and seizures (Krishnan et al, 2015; Pantazopoulos

& Berretta, 2016; Sorg et al, 2016; Wen et al, 2018a,b). For exam-

ple, preclinical studies and the analysis of human post-mortem

samples of schizophrenic patients showing reductions in aggrecan

and WFA staining suggested that PNN alterations could be a key

component of the pathophysiology of psychiatric disorders (Panta-

zopoulos et al, 2010, 2015). On the other hand, several works

have demonstrated that the reduction in PNNs can be used to

promote plasticity during aging and recovery from brain lesions

(Hill et al, 2012; Soleman et al, 2012; Gherardini et al, 2015;

Wiersma et al, 2017; Fawcett et al, 2019). Moreover, the miR-29

family is acutely neuroprotective in stroke models (Khanna et al,

2013; Ouyang et al, 2013; Kobayashi et al, 2019), and it has been

found to be downregulated in human post-mortem samples of

Alzheimer disease, Huntington disease, bipolar disorders, and

schizophrenia (Hebert et al, 2008; Johnson et al, 2008; Geaghan &

Cairns, 2015). Thus, considering that antimiRs and miRNA mimics

are under clinical trials for different human pathologies (Rupai-

moole & Slack, 2017), modulation of miR-29 family levels could

represent a novel and concrete strategy for treating a variety of

brain diseases.

◀ Figure 6. Manipulations of miR-29a levels promote changes in PNNs.

A Images of WFA-labeled PNNs of scrambled-treated visual cortex (left) and miR-29a mimic (right) in young mice. Scale bar 60 lm.B, C Quantification of PNN density (scr vs. mim29a, N = 3 mice per group; t-test, P = 0.20) and intensity for each animal (scr vs. mim29a, N = 3 mice per group; t-test,

P = 0.014).D Cumulative frequency of PNN staining intensity in scrambled- and mimic-treated young mice scr (N = 1,438 cells vs. mim29a N = 1,749 cells, Kolmogorov–

Smirnov test, P < 0.0001).E PNN distribution in classes of intensity in mice treated with scrambled and mimic 29a.F Images of WFA-labeled PNNs of scrambled-treated visual cortex (left) and amiR-29a LNA (right) in adult mice. Scale bar 60 lm.G, H Quantification of PNN density (scr vs. amiR-29a, N = 3 mice per group; t-test, P = 0.03) and intensity for each animal (scr vs. amiR-29a, N = 3 mice per group; t-

test, P = 0.047).I Cumulative frequency of PNN intensity in scrambled and amiR-29a-treated adult mice. scr N = 1,883 cells vs. amiR-29a N = 1,937 cells, Kolmogorov–Smirnov test,

P < 0.0001.J PNN distribution in classes of intensity in mice treated with scrambled and amiR-29a.K Biochemical quantification of C4S in adult amiR-29a-treated mice (N = 5) as compared to scrambled animals (N = 4). t-test, P = 0.0008.L Example of arylsulfatase B (ArsB) Western blot. Left: The lanes corresponding to the treated (treat scr or treat amiR-29a) and untreated (untreat scr or untreat

amiR-29a) cortex (ctx) of two amiR-29a-treated and two scr-treated mice are reported. Right: Quantification of the data shows ArsB upregulation by amiR-29a. Theresults are expressed as fold change normalized to untreated cortex. Each symbol represents the result of one animal. N = 4, scr vs. amiR-29a-treated cortex,unpaired t-test, P = 0.043 Data information: Error bars represent �SEM. Asterisk statistical significance, *P < .05 **P < 0.001.

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Debora Napoli et al EMBO reports

Materials and Methods

Animals

Mice used in all the experiments were of the C57BL/6J strain.

Animals were maintained at 22°C under a 12-h light–dark cycle (av-

erage illumination levels of 1.2 cd/m2) and housed in standard

cages according to current regulations about animal welfare. Food

(4RF25 GLP Certificate, Mucedola) and water were available ad libi-

tum. All experiments were carried out in accordance with the Euro-

pean Directive of 22 September 2010 (EU/63/2010) and were

approved by the Italian Ministry of Health. All tissue explants were

performed at the same time of the day (10–12 am).

Light manipulation

Mice were either born and raised in darkness or they were trans-

ferred to a dark room at P10 (before eye opening). At P25, they were

sacrificed; the procedure was carried out with the use of infrared

binoculars and eyes covered with black tape. P25 normally reared

were used as controls. To test the effects of one week of darkness

experiments, mice were transferred at P29 in a dark room for a

week. After this period, a group (0 h) was sacrificed in the dark as

previously described and another group (4 h) was sacrificed after

4 h of re-exposure to light. Controls were P36 mice that were always

kept under a 12-h dark-to-light cycle. Visual cortices were taken and

processed to perform molecular analyses.

Monocular deprivation

P25 or P120 mice were anesthetized with isoflurane (Forane, 3%).

Monocular deprivation was then accomplished by eyelid suture of

the right eye. In the days following the procedure, mice were kept in

a controlled environment and checked daily to ensure that the lids

remained closed. For molecular analyses, right and left cortices of

each animal were processed separately.

Stereotaxic injections

Mice were anesthetized with isoflurane (Forane, 3%) and fixed

on a stereotaxic support through the use of metal bars in the

ears. The skin was removed, and perforations were produced in

the skull using a surgical drill around binocular visual cortex

area. A glass microcapillary (100-lm tip), was inserted into the

cortex to inject miR-29a mimic and antagonist or scrambled

sequences. Injections were performed at three sites surrounding

the binocular visual cortex identified by previous IOS imaging of

visual responses. The skin was subsequently sutured, and physi-

ological solution was injected subcutaneously to prevent dehy-

dration. Moreover, paracetamol was administered in water

ad libitum for two days.

Immunohistochemistry

Mice were anesthetized with chloral hydrate (1 ml/50 g) and

perfused via intracardiac infusion with PBS and then 4%

paraformaldehyde (PFA, wt/vol, dissolved in 0.1 M phosphate

buffer, pH 7.4). Brains were quickly removed and post-fixed

overnight in PFA, then transferred to 30% sucrose (wt/vol), 0.05%

sodium azide (wt/vol) solution, and finally stored at 4°C. 45-lmcoronal sections were cut on a freezing microtome (Leica), and free-

floating sections were processed for immunohistochemistry. Slices

of visual cortex were pre-incubated 2 h at RT in blocking solution of

3% bovine serum albumin (BSA) in PSB and incubated O/N at 4°C

with a PBS solution of Fluorescein Wisteria floribunda lectin

(Biotinylated Wisteria floribunda lectin, Vector Laboratories, 1:400).

Then, slides were rinsed three times in PBS (10 min each) at RT and

incubated for 2 h 30 min with a PBS solution of fluorescent strepta-

vidin (Streptavidin Alexa Fluor 488 conjugate, Thermo Fisher Scien-

tific, 1:400). Finally, slides were rinsed three times with PBS and

used for parvalbumin staining. A pre-incubation in a blocking solu-

tion of 3% BSA plus 0.2% of Triton in PBS was done at RT for 2 h.

Slices were incubated O/N at 4°C in the primary antibody solution

of anti-parvalbumin (Swant, cat. no. 235, 1:300). Slices were then

rinsed three times in PBS (10 min each) and incubated with a

secondary antibody (Alexa Fluor 555 conjugate, Thermo Fisher

Scientific, 1:400) for 2 h 30 min at RT. Slices were then rinsed three

times in PBS (10 min each), coverslipped in mounting medium

(VECTASHIELD� antifade mounting medium, Vector Laboratories,

cat.no. H-100), and stored at 4°C until acquisition section.

In situ hybridization

Mice were perfused, and slides were produced as previously

described for immunostaining protocol. Then, in situ hybridization

was performed using the following protocol:

1st day: Free-floating sections were washed with PBS 0.1% Tween-

20 (PBT) tree times for 5 min and treated with 1:20,000 proteinase

K (20 mg/ml) in PBT for 10 min at RT. The reaction was blocked by

washing two times with glycine 2 mg/ml in PBT at RT. Slices were

re-fixed with 4% paraformaldehyde for 20 min at RT and washed

three times in PBT. Slices were prehybridized 30 min at 48°C in

hybridization buffer [HB, 50% formamide (Sigma, cat.no. F9037),

5× SSC (20× SSC: 3 M NaCl, 0.3 M trisodium citrate in H2O), 0.1%

Tween-20, 50 ug/ml Heparin (Sigma, cat.no. H3393), 500 ug/ml

torula yeast RNA]. Sections were hybridized at 37°C overnight (O/

N) with 80 nM of LNA probe to miR-29a (mmu-miR-29a-3p, Qiagen,

cat.no. 339111YD00616795-BCF)

2nd day: Slices were washed twice with 2× SSC and once with 0.2×

SSC at RT for 10 min and blocked 30 min at RT in blocking solution

[1% blocking reagent (Roche, cat.no. 11096176001), 1% sheep

serum in MABT (100 mM maleic acid, 150 mM NaCl at pH 7.5,

0.1% Tween-20]. Sections were incubated with Anti-Dig-AP Fab

fragments Ab 1:2000 (Roche, cat.no. 11093274910) in blocking solu-

tion O/N at 4°C.

3rd day: Slices were washed three times with PBT (15 min) and

three times with NMNT (100 mM NaCl, 100 mM Tris–HCl pH 9.5,

50 mM MgCl2, 0.1% Tween-20, 2 mM tetramisole). Sections

were incubated NBT/BCIP (1 tablet in 10 ml dH2O, Roche

cat.no.11697471001), and the staining reaction was controlled every

10 min. The same slides were used for immunostaining against

parvalbumin and a neuronal marker. After three washes on PBT,

slides were directly incubated O/N 4°C in a primary antibody solu-

tion anti-parvalbumin (synaptic system, cat.no. 195 004, 1:250) and

anti-NeuN (cell signaling, cat.no. 94403S, 1:300) with 1.5% BSA in

PBS + 0.2% Triton.

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EMBO reports Debora Napoli et al

4th day: Slides were washed three times in PBT and incubated for

2 h 30 min at RT with secondary antibody solution [anti-mouse

Alexa Fluor 488 (1:400) and anti-pig Alexa Fluor 546 (1:400) with

BSA 1.5% in PBT]. Finally, slides were washed in PBT and mounted

using a medium with DAPI (Vector Laboratories, VECTASHIELD�

Antifade Mounting Medium with DAPI, cat.no. H-1200).

Image acquisition

Images from the visual cortex were acquired with an ApoTome.2

microscope (Zeiss, Oberkochen, Germany). Treated cortices were

recognized by a tissue incision. Three z-stack sections per slide and

at least five slides per animal were obtained with a 20× objective.

Laser intensity and exposure time were calculated by a pre-acquisi-

tion section and were the same for all acquisitions. Then, a weak

Fourier filter was applied, and then, the “Maximum projection”

function was used to obtain a single image per stack. The number of

positive PNNs and PV was counted using ImageJ, and a MATLAB

script was elaborated to analyze density and intensity. A small

(60 × 60 px) image of each cell has been extracted. Pixels belonging

to the PNN have been selected with Otsu’s binarization method.

PNN intensity was defined as the average of the intensity values of

all the pixels belonging to a PNN. The intensity value of every PNN

of the treated hemisphere was normalized to the average PNN inten-

sity of the same animal and same slice on the untreated hemisphere.

For every field, a cell density (PNN/mm2) was calculated and the

value was normalized to the average PNN density of the same

animal and same slice on untreated hemisphere. To calculate PNN

distribution in classes, the distribution of normalized values of

intensity of all the left hemisphere PNNs was divided into three

equal parts was assigned the labels of faint, medium, and strong

PNNs. The number of cells belonging to each class was pooled

across all the animals for each treatment, and statistical analyses

were performed. The same approach was used to quantify miR29a

in situ hybridization experiments.

RNA extraction and quantification (qPCR)

Tissue samples were homogenized in cell disruption buffer

(Ambion). RNA was extracted by the addiction of Phenol/guani-

dine-based QIAzol Lysis Reagent (Qiagen, cat. no. 79306). Chloro-

form was added, and the samples were shacked for 15 s. The

samples were left at 20–24°C for 3 min and then centrifuged

(12,000 g, 20 min, 4°C). The upper phase aqueous solution,

containing RNA, was collected in a fresh tube, and the RNA was

precipitated by the addiction of isopropanol. Samples were mixed

by vortexing, left at 20–24°C for 15 min and then centrifuged

(12,000 g, 20 min, 4°C). Supernatant was discarded, and the RNA

pellet was washed in 75% ethanol by centrifugation (7500 g,

10 min, 4°C). Supernatant was discarded, and the pellet was left to

dry for at least 15 min; then, it was resuspended in RNAse-free

water. Total RNA concentrations were determined by NanoDrop

Spectrophotometer (Thermo Scientific 2000 C). RNA quality was

analyzed through a gel running (1% agarose). Total RNA was

reverse transcribed using the QuantiTeck Reverse Transcription Kit

(Qiagen, cat. no. 205311), and miRNAs were reverse transcribed

using TaqMan MicroRNA reverse transcription kit (Thermo

Fisher, cat. no. 4366596). Gene expression was analyzed by

real-time PCR (Step one, Applied Biosystems). TaqMan inventoried

assays were used for miR-29a-3p (assay ID: 002112), sno234 (assay

ID:001234), Dnmt3a (Mm00432881_m1), Npas4 (Mm012207866_g1),

Bdnf exIV (Mm00432069_m1), Gadd45a (Mm00532802_m1),

Gadd45b (Mm00435121_g1), Tet3 (Mm 00805756_m1), Mmp2

(Mm00439498_m1), Mmp9 (Mm00442991_m1), and Mmp13

(Mm00439491_m1). TaqMan assay was used for glyceraldehyde 3-

phosphate dehydrogenase (Gapdh), GAPDH probe ATCCCAGAGCT

GAACGG, GADPH forward CAAGGCTGTGGGCAAGGT, and GADPH

reverse GGCCATGCCAGTGAGCTT. Quantitative values for cDNA

amplification were calculated from the threshold cycle number (Ct)

obtained during the exponential growth of the PCR products.

Threshold was set automatically by the Step one software. Data

were analyzed by the DDCt methods using GAPDH or SNO234 to

normalize the cDNA levels of the transcripts under investigation.

Western blotting

Visual cortices were collected and frozen on dry ice. The tissue

samples were homogenized in cell disruption buffer (Ambion) and

spun down for 5 min at 14,000 g at 4°C, and the supernatant was

recovered. Protein concentration was determined by Bradford assay

(Bio-Rad). For the running, each sample was boiled and 40 lg of

protein extracts were loaded in each lane of a 4–12% acrylamide

gels, using the Precast gel System (Bio-Rad). The samples were blot-

ted onto nitrocellulose membrane (Bio-Rad) using Tans-Turbo Blot

(Transfer system) apparatus (Bio-Rad), washed four times in phos-

phate-buffered saline (PBS) with 0.1% Tween-20, and blocked for

2 h at room temperature (RT) using Blocking Odyssey Solution (LI-

COR 927-40000). Then, the nitrocellulose membrane was incubated

with the antibodies to DNMT3a (Abcam, cat. no. ab13888; 1:300),

ARSB (Thermo Fisher, cat.no. MA524327, 1:500), and beta-tubulin

(Sigma-Aldrich, cat. no. T4026, 1:3,000). Antibodies were diluted in

Blocking Odyssey Solution and PSB (1:1) with 0.2% Tween-20 and

incubated overnight (O/N) at 4°C. Blots were than washed three

times in PBS 0.1% Tween-20 and incubated with, respectively,

IRDye 800CW and IRDye 680RD secondary antibodies diluted in

Blocking Odyssey Solution and PSB (1:1) with 0.2% Tween-20 and

0.01% SDS for 2 h at RT (1:20,000). Finally, blots were washed for

four times in PBS with 0.1% Tween-20 and one time with PBS only.

Acquisitions were done using Odyssey LI-COR machinery.

RNA-seq

Total RNA is extracted, prepared, and sequenced on Illumina HiSeq

instrument during a pair-end read 125 bp sequencing, producing

sequencing result in FastQ format. The FastQ files are processed

through the standard Tuxedo protocol [ref1], outputting the FPKM

values for each gene of each replicate. The differential analysis of the

FPKM values across all experiment and control groups is conducted

with Cyber-T, a differential analysis program using Bayesian-regularized

t-test (Baldi & Long, 2001; Kayala & Baldi, 2012). The P-value threshold

used for determining differential expression is 0.05 for all groups.

Sample preparation for proteome analysis

Binocular visual cortices were collected and snap-frozen in liquid

nitrogen. On preparation for MS, protein amount was estimated

ª 2020 The Authors EMBO reports e50431 | 2020 13 of 19

Debora Napoli et al EMBO reports

based on fresh tissue weight (assuming 5% of protein w/w) and

lysis buffer (4% SDS, 100 mM HEPES, pH 8, 1 mM EDTA, 100 mM

DTT) was added accordingly to a final concentration of 1 lg/ll.Samples were then vortexed (5 times) prior to sonication (Bioruptor

Plus, Diagenode) for 10 cycles (30 s ON/60 s OFF) at high setting, at

4°C. The samples were then centrifuged at 3,000 g for 5 min at

room temperature, and the supernatant transferred to 2-ml Eppen-

dorf tubes. Reduction (15 min, 45°C) was followed by alkylation

with 20 mM iodoacetamide (IAA) for 30 min at room temperature

in the dark. Protein amounts were confirmed, following an SDS–

PAGE gel of 4% of each sample against an in-house cell lysate of

known quantity. 100 lg protein of each sample was taken along for

digestion. Proteins were precipitated overnight at 20°C after addition

of a 4× volume (400 ll) of ice-cold acetone. The following day, the

samples were centrifuged at 20,800 g for 30 min at 4°C and the

supernatant carefully removed. Pellets were washed twice with

500 ll ice-cold 80% (v/v) acetone in water then centrifuged at

20,800 g at 4°C. They were then allowed to air-dry before addition

of 50 ll of digestion buffer (3M Urea, 100 mM HEPES, pH 8).

Samples were resuspended with sonication (as above), LysC (Wako)

was added at 1:100 (w/w) enzyme:protein and digestion proceeded

for 4 h at 37°C with shaking (1,000 rpm for 1 h, then 650 rpm).

Samples were then diluted 1:1 with Milli-Q water and trypsin

(Promega) added at the same enzyme to protein ratio. Samples were

further digested overnight at 37°C with shaking (650 rpm). The

following day, digests were acidified by the addition of TFA to a

final concentration of 2% (v/v) and then desalted with Waters

Oasis� HLB lElution Plate 30 lm (Waters Corporation, Milford,

MA, USA) in the presence of a slow vacuum. In this process, the

columns were conditioned with 3 × 100 ll solvent B (80% (v/v)

acetonitrile; 0.05% (v/v) formic acid) and equilibrated with

3 × 100 ll solvent A (0.05% (v/v) formic acid in Milli-Q water).

The samples were loaded, washed three times with 100 ll solventA, and then eluted into 0.2-ml PCR tubes with 50 ll solvent B. Theeluates were dried down with the speed vacuum centrifuge and

dissolved at a concentration of 1 lg/ll in reconstitution buffer (5%

(v/v) acetonitrile, 0.1% (v/v) formic acid in Milli-Q water). For

data-independent analysis (DIA), peptides were spiked with reten-

tion time iRT kit (Biognosys AG, Schlieren, Switzerland) prior to

analysis by LC-MS/MS.

Data acquisition for label-free analysis of monocular deprivedyoung and adult treated with amiR29-a animals

For experiments, 500 ng of peptides was separated using the

nanoAcquity UPLC system (Waters) fitted with a trapping (nanoAc-

quity Symmetry C18, 5 lm, 180 lm × 20 mm) and an analytical

column (nanoAcquity BEH C18, 1.7 lm, 75 lm × 250 mm). The

outlet of the analytical column was coupled directly to an Orbitrap

Fusion Lumos (Thermo Fisher Scientific) using the Proxeon nanos-

pray source. Solvent A was water, 0.1% (v/v) formic acid, and

solvent B was acetonitrile, 0.1% (v/v) formic acid. The samples

(500 ng) were loaded with a constant flow of solvent A at 5 ll/min

onto the trapping column. Trapping time was 6 min. Peptides were

eluted via the analytical column with a constant flow of 0.3 ll/min.

During the elution step, the percentage of solvent B increased in a

linear fashion from 3% to 25% in 30 min, then increased to 32% in

5 more min and finally to 50% in a further 0.1 min. Total runtime

was 60 min. The peptides were introduced into the mass spectrome-

ter via a Pico-Tip Emitter 360 lm OD × 20 lm ID; 10 lm tip (New

Objective), and a spray voltage of 2.2 kV was applied. The capillary

temperature was set at 300°C. The RF lens was set to 30%. Full-scan

MS spectra with mass range 375–1,500 m/z were acquired in profile

mode in the Orbitrap with resolution of 120,000 FWHM. The filling

time was set at maximum of 50 ms with limitation of 2 × 105 ions.

The “Top Speed” method was employed to take the maximum

number of precursor ions (with an intensity threshold of 5 × 103)

from the full-scan MS for fragmentation (using HCD collision

energy, 30%) and quadrupole isolation (1.4 Da window) and

measurement in the ion trap, with a cycle time of 3 s. The MIPS

(monoisotopic precursor selection) peptide algorithm was employed

but with relaxed restrictions when too few precursors meeting the

criteria were found. The fragmentation was performed after accu-

mulation of 2 × 103 ions or after filling time of 300 ms for each

precursor ion (whichever occurred first). MS/MS data were acquired

in centroid mode, with the Rapid scan rate and a fixed first mass of

120 m/z. Only multiply charged (2 + - 7 +) precursor ions were

selected for MS/MS. Dynamic exclusion was employed with maxi-

mum retention period of 60s and relative mass window of 10 ppm.

Isotopes were excluded. Additionally only 1 data-dependent scan

was performed per precursor (only the most intense charge state

selected). Ions were injected for all available parallelizable time. In

order to improve the mass accuracy, a lock mass correction using a

background ion (m/z 445.12003) was applied. For data acquisition

and processing of the raw data, Xcalibur 4.0 (Thermo Scientific) and

Tune version 2.1 were employed.

Data-independent acquisition for adult animals treatedwith amiR-29a

Peptides were separated using the nanoAcquity UPLC system

(Waters) with a trapping (nanoAcquity Symmetry C18, 5 lm,

180 lm × 20 mm) and an analytical column (nanoAcquity BEH

C18, 1.7 lm, 75 lm × 250 mm). The outlet of the column was

coupled to a QEHFX (Thermo Fisher Scientific) using the Proxeon

nanospray source. Solvent A was water, 0.1% FA, and solvent B

was acetonitrile, 0.1% FA. Samples were loaded at constant flow of

solvent A at 5 ll/min onto the trap for 6 min. Peptides were eluted

via the analytical column at 0.3 ll/min and introduced via a Pico-

Tip Emitter 360 lm OD × 20 lm ID; 10 lm tip (New Objective). A

spray voltage of 2.2 kV was used. During the elution step, the

percentage of solvent B increased in a non-linear fashion from 0%

to 40% in 120 min. The capillary temperature was set at 300°C. The

RF lens was set to 40%. Data from a subset of samples were

acquired in DDA in order to create a spectral library. MS conditions

were as follows: Full-scan spectra (350–1,650 m/z) were acquired

in profile mode in the Orbitrap with resolution of 60,000. The fill

time was set to 50 ms with limitation of 2 × 105 ions. The

“TopN = 15” method was employed to take the precursor ions (with

an intensity threshold of 5 × 104) from the full-scan MS for frag-

mentation (using HCD collision energy, 30%) and quadrupole isola-

tion (1.4 Da window) and measurement in the Orbitrap (resolution

15,000, fixed first mass 120 m/z), with a cycle time of 3 s. MS/MS

data were acquired in profile mode (QEHFX). Only multiply charged

precursor ions were selected. Dynamic exclusion was employed

(15s and relative mass window of 10 ppm). Isotopes were excluded.

14 of 19 EMBO reports e50431 | 2020 ª 2020 The Authors

EMBO reports Debora Napoli et al

For data acquisition and processing of the raw data, Xcalibur 4.0

(Thermo Scientific) and Tune version 2.9 were employed. For the

DIA data acquisition, the same gradient conditions were applied to

the LC as for the DDA and the MS conditions were varied as

described: Full-scan MS spectra with mass range 350–1,650 m/z

were acquired in profile mode in the Orbitrap with resolution of

120,000. The filling time was set at maximum of 20 ms with limita-

tion of 5 × 105 ions. DIA scans were acquired with 34 mass window

segments of differing widths across the MS1 mass range with a cycle

time of 3 s. HCD fragmentation (30% NCE) was applied, and MS/

MS spectra were acquired in the Orbitrap with a resolution of

30,000 over the mass range 200–2,000 m/z after accumulation of

2 × 105 ions or after filling time of 70 ms (whichever occurred

first). Ions were injected for all available parallelizable time. Data

were acquired in profile mode.

Data analysis of label-free analysis monocular deprived youngand adult treated with amiR29-a animals

The Andromeda search engine (Cox et al, 2011), part of MaxQuant

(version 1.5.3.28; Cox & Mann, 2008), was used to search the data.

The data were searched against a species-specific (Mus musculus

Swiss-Prot) database and a list of common contaminants. The data

were searched with the following modifications: carbamidomethyl

(C) (fixed), and oxidation (M) and acetyl (protein N-term; variable).

The mass error tolerance for the full-scan MS spectra was set at

20 ppm and for the MS/MS spectra at 0.5 Da. A maximum of two

missed cleavages were allowed. Peptide and protein level 1% FDR

were applied. LFQ (label-free quantification) values from the

MaxQuant output were used to perform differential protein expres-

sion analysis using scripts written in R (v3.4.1). After removal of

reverse and contaminant hits, only protein groups quantified by at

least two unique peptides were retained. Protein differential expres-

sion was evaluated using the limma package (Ritchie et al, 2015).

Differences in protein abundances were statistically determined

using Student’s t-test moderated by the empirical Bayes method. P

values were adjusted for multiple testing using the Benjamini–Hoch-

berg method (FDR, denoted as “q”).

DIA data analysis of adult animals treated with amiR-29a

For library creation, the DDA and DIA data were searched using

Pulsar in Spectronaut Professional+ (version 12.0.20491.0.21234,

Biognosys AG, Schlieren, Switzerland). The data were searched

against a species-specific (Mus musculus Swiss-Prot) database and a

list of common contaminants. The data were searched with the

following modifications: carbamidomethyl (C) (Fixed) and oxidation

(M)/ acetyl (protein N-term; variable). A maximum of two missed

cleavages for trypsin were allowed. The identifications were filtered

to satisfy FDR of 1% on peptide and protein level. The generated

library contained 74,254 precursors, corresponding to 4,729 protein

groups. Relative quantification was performed in Spectronaut for

each pairwise comparison using the replicate samples from each

condition. Precursor matching, protein inference, and quantification

were performed in Spectronaut using default settings. The data (can-

didate table, SUP XX) were then exported, and further data analyses

and visualization were performed with R-studio using in-house

pipelines and scripts.

In vivo electrophysiology and Intrinsic optical imaging

For surgery, mice were sedated with isoflurane (Forane, 3%)

followed by urethane (0.7 g /kg, i.p., at 20% w/v in ringer). Dexam-

ethasone (Soldesam, 2mg/kg) was administered subcutaneously to

reduce secretions and edema. The animal was placed on a stereo-

taxic apparatus and maintained at 37.5 °C by a feedback-controlled

heating pad. The animal was also ventilated through an oxygen

mask. During surgery, eyes were protected by applying a dexametha-

sone-based ointment (Tobradex, tobramycin 0.3%, and dexametha-

sone 0.1%), then with a thin layer of silicon oil. Local anesthesia

was obtained with a subcutaneous injection of lidocaine (Angelini).

After exposing the skull, we performed a small craniotomy (2mm in

diameter) over the binocular visual cortex (2.8–3.3 mm lateral and

0.1 mm anterior to lambda) living dura mater intact. An electrode

(2 × 2-tet-3 mm-150-150-121-A16-15, NeuroNexus Technologies)

was slowly lowered into the cortex to an appropriate depth to record

local field potentials and single-unit activity and was allowed to

settle for 30–40min before the beginning of recordings. The record-

ing sites were located between layers III and V; therefore, the physio-

logical data recorded mostly reflect the properties of these layers. At

the end of the experiment, the animal was killed by overdose with of

urethane. Signals were acquired using 4-channel Neuralynx device,

and data analysis was performed using a custom software written in

MATLAB. Visual stimuli were generated in MATLAB using the

Psychophysics Toolbox extension and displayed with gamma correc-

tion on a monitor (Sony Trinitron G500, 60 Hz refresh rate, 32 cd

m�2 mean luminance) placed 20 cm from the mouse, subtending

60–75° of visual space. Local field potential—we measured the

contralateral-to-ipsilateral ratio of VEPs to measure OD plasticity.

Extracellular signal was filtered from 0.3 to 275 Hz and sampled at

30.3 kHz. VEPs in response to square wave patterns with a spatial

frequency of 0.03 c/deg and abrupt phase inversion (1 Hz temporal

period) were evaluated in the time domain by measuring the P1

peak-to-baseline amplitude and latency. We used computer

controlled mechanical shutters to collect data from each eye, reduc-

ing possible effects due to changes in behavioral states, and adapta-

tion. Intrinsic optical imaging recordings were performed under

isoflurane anesthesia (0.5–1%) supplemented with an intraperi-

toneal injection of chlorprothixene hydrochloride (1.25 mg/kg).

Images were obtained using an Olympus microscope (BX50WI). Red

light illumination was provided by eight red LEDs (625 nm, Knight

Lites KSB1385–1P) attached to the objective (Zeiss Plan-NEOFLUAR

5x, NA: 0.16) using a custom-made metal LED holder. The animal

was secured under the objective using a ring-shaped neodymium

magnet mounted on an arduino-based 3D printed imaging chamber

that also controls eye shutters and a thermostated heating pad (30).

Visual stimuli were generated using MATLAB Psychtoolbox and

presented on a gamma corrected 9.7-inch monitor, placed 10 cm

away from the eyes of the mouse. Contrast reversing Gabor patches

(temporal frequency: 4 Hz, duration: 1 s) were presented in the

binocular portion of the visual field (�10° to+10° relative to the

horizontal midline and �5° to+50° relative to the vertical midline)

with a spatial frequency of 0.03 cycles per degree, mean luminance

20 cd/m2, and a contrast of 90%. Visual stimulation was time

locked with a 16 bit depth acquisition camera (Hamamatsu digital

camera C11440) using a parallel port trigger. Interstimulus time was

14 s. Frames were acquired at 30 fps with a resolution of 512 × 512

ª 2020 The Authors EMBO reports e50431 | 2020 15 of 19

Debora Napoli et al EMBO reports

pixels, low-pass filtered with a 2D average spatial filter (30 pixels,

117 lm2 square kernel) and downsampled to 128 × 128 pixels. The

signal was averaged for at least eight groups of 20 trials and down-

sampled to 10 fps. The stimulated eye was alternated using eye shut-

ters between groups of trials in order to prevent biases due to

fluctuating levels of anesthesia for the contralateral and ipsilateral

eye. Fluctuations of reflectance (R) for each pixel were computed as

the normalized difference from the average baseline (DR/R). For

each recording, an image representing the mean evoked response

was computed by averaging frames between 0.5 and 2.5 s after stim-

ulation. A region of interest (ROI) was automatically calculated on

the mean image of the response, by selecting pixels in the lowest

30% DR/R of the range between the maximal and minimal intensity

value. Mean evoked responses were quantitatively measured as the

average intensity inside the ROI. To weaken background fluctua-

tions, a manually selected polygonal region of reference (ROR) was

subtracted. The ROR was placed where no stimulus response, blood

vessel artifact, or irregularities of the skull were observed.

Isolation of glycosaminoglycans (GAGs)

Procedures followed the work by Silpananta et al (1967) with slight

modifications. The collected tissue samples were homogenized in

cold extraction buffer (10 ul/mg of wet weight, buffer contains 4 M

guanidinium hydrochloride in 0.05 M sodium acetate, pH 5.8 with

protease inhibitors). Adjust the density of the homogenized samples

with cesium chloride to 1.72 mg/ml. The mixture was then

subjected to ultracentrifugation (120,000 g, 48 h, 4°C). The samples

were then collected into five equal fractions. The fractions were

dialyzed with 1× dialysis buffer (0.4 M guanidinium hydrochloride,

0.025 M sodium acetate, pH 5.8) overnight at 4°C. The negatively

charged GAGs were precipitated by the addition of 0.1 volume of

5% (w/v) cetylpyridinium chloride (CPC) and kept at 4°C for 2 h.

The samples were then centrifuged at 4,500 rpm for 30 min.

Dissolved the pellet in 100 ll if deionized water and stored at

�20°C. The amount of GAGs was quantified by CPC turbidimetry.

Chondroitinase ABC (ChABC) treatment anddisaccharide conjugation

The isolated GAG was treated with ChABC to cleave the long GAG

chains into disaccharide units. 5 lg of samples was digested with

100 mU of ChABC in 100 mM NH4Ac buffer, pH 7.0 for 16 h at 37°C.

Following the enzyme treatment, the digested disaccharides were recov-

ered from the supernatant after ethanol precipitation for 16 h at 4°C and

centrifugation. The supernatant was dried in a 50°C oven for 16 h. For

disaccharide derivatization, 10 ll of 12.5 mM 2-aminoacridone (AMAC;

dissolved in 3:17 acetic acid/DMSO) was used to dissolve the dried

disaccharide preparations, and then, 10 ll of 1.25 M sodium cyanoboro-

hydride was then added. For standard disaccharides, 5 lg of each disac-

charide was used for the derivatization. The sample mixtures were

incubated in dark for 16 h at 37°C. 10 ll of 30% glycerol was added to

the samples, and the derivatized disaccharides were kept at�20°C.

Fluorophore-assisted carbohydrate electrophoresis (FACE)

A mini-gel of 40% polyacrylamide was prepared in Tris borate

buffer (0.1 M Tris buffer titrated with boric acid to pH 8.3). 10 ll

of AMAC-tagged disaccharides was diluted with 10 ll of FACE

solvent (2:1:7 DMSO:glycerol:water) before loading into the gel.

For the standard disaccharides, 1:8 dilution with the FACE solvent

was necessary. The gel was electrophoresed at a constant voltage

of 1,000 V for about 110 min, with 4°C cooling water bath to

prevent overheating. The gel was illuminated with UV light and

visualized at 405 nm in a UVP Bioimaging System. Integrated

densities (ID) of the bands were measured by the software ImageJ.

Standard curve was set up by measuring the ID of the disaccharide

standards, and the amount of individual sulphated disaccharides

was thus calculated. Results are presented as ng of C4S per lg of

isolated GAGs.

Data availability

The datasets produced in this study are available in the following

databases:

RNA-seq data: Gene Expression Omnibus GSE141734 (https://

www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46843).

Proteomic data: ProteomeXchange Consortium via the PRIDE part-

ner repository PXD016430 (http://proteomecentral.proteomexcha

nge.org/cgi/GetDataset?ID=PXD016430) and PXD016358 (http://pro

teomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD016358)

Expanded View for this article is available online.

AcknowledgementsWe thank Enrica Strettoi for help with microscopy, and Christophe Magnan,

Laura Baroncelli, Francesco Calugi, Sara Cornuti, Elena Novelli, and Aurelia

Viglione for discussions about data analysis and experimental protocols. Fund-

ing was provided by EPIGEN flagship project and PRIN 2017HMH8FA project.

Author contributionsAC, DN, and TP conceptualized the study; AC, JCFK, TP, LL, RM, GS, and PB

contributed to methodology; DN, EP, LL, GS, EKS, JK, PT, ETT, PB, SB, and JCFK

investigated the study; DN, AC, and TP wrote—original draft; AC, JCFK, PB, and

TP involved in funding acquisition; AC, TP, and PB contributed to resources;

MS, SC, PB, and AC curated the data; AC, PB, and TP supervised the study.

Conflict of interestThe authors declare that they have no conflict of interest.

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